Data Science Blog

Month: September 2016

Today I gave a talk in our Weekly AI meeting on the topic of ControCurator. This is a project that I am currently working on, which has the goal to enable the discovery and understanding of controversial issues and events by combining human-machine active learning workflows.

In the talk I explained the issue of defining the space of a controversy, and how this relates to for instance wicked problems. You can see the slides below.

Brainstem tumors are a rare form of childhood cancer for which there is currently no cure. The Semmy Foundation aims to increase the survival of children with this type of cancer by supporting scientific research. The Center for Advanced Studies at IBM Netherlands is supporting this research by developing a cognitive system that allows doctors and researchers to quicker analyse MRI-scans and better detect anomalies in the brainstem.

In order to gather training data, a crowdsourcing event was held at the festival Lowlands, which is a 3-day music festival that took place from 19-21 August 2016 and welcomed 55k visitors. At the science fair, IBM had a booth that hosted both this research and showcase of the Weather stations of the Tahmo project with TU Delft.

In the crowdsourcing task, the participants were asked to draw the shape of the brainstem and tumor in an MRI scan. Gathering data on whether a particular layer of a scan contains the brainstem and determining its size should allow a classifier to recognize the tumors. Furthermore, the annotator quality can be measured with the CrowdTruth methodology by analysing the precision of the edges that were drawn in relation to their alcohol and drug use that we collected. The hypothesis is that people under influence can still make valuable contributions, but that these are of lower quality than sober people. This may make the reliability of online crowd workers more clear, because it is unknown under what conditions they make their annotations.

The initial results in the heatmap of drawn pixels give an indication of the overall location of the brainstem, but further analysis will follow on the individual scans in order to measure the worker quality and generating 3d models.